# Xiaohongshu / RedNote Scraper & Intelligence (`scrupulous_buckler/xiaohongshu-brand-influencer-discovery`) Actor Scrape or analyze Xiaohongshu and RedNote notes and comments for content opportunities, creator audits, competitor comparisons, consumer voice insights, and market maps. Use uploaded datasets without cookies or collect notes with your own session. - **URL**: https://apify.com/scrupulous\_buckler/xiaohongshu-brand-influencer-discovery.md - **Developed by:** [Peng Lyu](https://apify.com/scrupulous_buckler) (community) - **Categories:** Social media, AI, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.99 / 1,000 xiaohongshu note results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Xiaohongshu / RedNote Scraper & Intelligence Not another generic RedNote scraper. This Actor turns Xiaohongshu notes into evidence-linked content opportunities, creator audits, competitor comparisons, consumer-voice reports, and market maps. ### Intelligence modes - `demo`: run a stable no-Cookie example before supplying any data - `topicRadar`: rank proven content examples and suggest actionable angles - `consumerVoice`: identify consumer questions, concerns, comparison criteria, mentioned entities, and evidence-backed content directions - `marketMap`: map named brands, products, ingredients, devices, medicines, foods, and lifestyle alternatives inside the supplied discussions - `creatorAudit`: calculate a creator's engagement baseline, breakout rate, content themes, strongest notes, and data-quality warnings - `brandCompare`: compare two to five brands by content share, engagement share, breakout rate, themes, and differentiators All intelligence modes accept existing note JSON exported from other Actors. Consumer voice and market map also accept existing comment JSON or plain comment strings. Customers can keep their preferred data provider and buy only the analysis. They can alternatively provide their own Xiaohongshu Cookie and collect notes through this Actor. ### MVP boundary Collection modes: - `search`: collect notes matching a keyword - `userPosts`: collect a creator's public posts - `note`: collect one note by URL or ID - `snapshot`: parse supplied HTML snapshots or attempt public note pages The first three modes require the customer's own Xiaohongshu Cookie, entered in Apify's secret input field. The Cookie is used only for the run and is never written to logs or datasets. Residential proxy configuration is supported and recommended for authenticated runs. The Actor is read-only. It does not like, comment, follow, publish, bypass CAPTCHAs, or attempt to defeat access controls. ### Topic radar without a Cookie ```json { "mode": "topicRadar", "query": "防晒", "uploadedNotes": [ { "noteId": "note-1", "title": "敏感肌防晒避坑", "url": "https://www.xiaohongshu.com/explore/note-1", "creatorName": "示例作者", "likes": 5200, "comments": 320, "collects": 2100, "shares": 180, "hashtags": ["防晒", "敏感肌"] } ], "maxOpportunities": 10 } ```` Uploaded data is processed for the current run and is not treated as a login credential. ### Consumer voice and market map Use `consumerVoice` when the question is "What are customers really discussing, asking, and worrying about?" Use `marketMap` when the question is "Which brands, products, ingredients, and alternatives exist in the customer's mind?" ```json { "mode": "consumerVoice", "query": "血糖管理", "regulatedTopic": true, "knownEntities": [ "客户品牌", "竞品甲", "竞品乙", "某种成分", "血糖仪", "饮食管理" ], "uploadedNotes": [ { "noteId": "note-1", "title": "餐后血糖管理记录", "description": "记录饮食、运动和产品选择时遇到的问题。", "likes": 800, "comments": 120, "collects": 350 } ], "uploadedComments": [ { "commentId": "comment-1", "noteId": "note-1", "text": "这个成分和竞品甲有什么区别？价格贵不贵？" }, { "commentId": "comment-2", "noteId": "note-1", "text": "我更想先调整饮食和运动，什么时候需要咨询医生？" } ] } ``` For regulated health and other sensitive topics, claim-risk output is a screening aid only. It does not provide medical, legal, advertising, or regulatory approval. ### What it returns Collection modes return one normalized row per successful note. Intelligence modes return report rows with source-linked evidence. Depending on the selected mode, reports include: - evidence-linked consumer questions and discussion dimensions - named brand, product, ingredient, and alternative mention counts - comparison dimensions such as results, safety, ingredients, price, usage, experience, trust, and alternatives - content and engagement share across competitor datasets - creator baselines, breakout rates, dominant themes, and strongest notes - content directions tied to observed evidence - coverage warnings when too few notes or no comments were supplied - claim-risk matches and safer framing for regulated topics Outputs describe patterns in the supplied dataset. They do not infer private attributes, diagnose individuals, or guarantee that a sample represents the whole market. ### Example input ```json { "mode": "search", "cookie": "a1=...; web_session=...; webId=...;", "query": "防晒", "brandKeywords": ["防晒", "敏感肌"], "maxItems": 100, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ``` For local fixture testing: ```json { "mode": "snapshot", "htmlSnapshots": [ { "url": "https://www.xiaohongshu.com/explore/demo-note", "html": "..." } ], "brandKeywords": ["防晒"] } ``` For creator posts: ```json { "mode": "userPosts", "cookie": "a1=...; web_session=...; webId=...;", "userUrlOrId": "https://www.xiaohongshu.com/user/profile/USER_ID", "maxItems": 50 } ``` ### Output example ```json { "noteId": "demo-note", "url": "https://www.xiaohongshu.com/explore/demo-note", "title": "敏感肌防晒实测", "creatorName": "示例作者", "likes": 1280, "comments": 86, "collects": 402, "shares": 31, "matchedKeywords": ["防晒", "敏感肌"], "discoveryScore": 87, "scoreReasons": [ "strong public engagement", "multiple requested keywords matched", "substantive note text" ], "sourceType": "public-note-page" } ``` ### Local development ```bash python3 -m unittest discover -s tests -v ``` To run as an Actor after installing dependencies: ```bash pip install -r requirements.txt python3 -m src ``` ### Monetization recommendation The Actor uses pay-per-event pricing: | Event | Price | | --- | ---: | | Successfully parsed note | $0.00599 | | Ranked content opportunity | $0.05 | | Creator performance audit | $0.49 | | Two-to-five-brand comparison | $1.49 | | Consumer voice report | $1.49 | | Consumer market map | $1.49 | Blocked, empty, duplicated, and invalid collection results are not charged. Platform usage and Apify's small automatic events may still appear separately in the run cost summary. ### Responsible use Only collect data you are authorized to process. Follow applicable platform terms and privacy, advertising, and data-protection laws. Do not use the output for harassment, sensitive profiling, or automated decisions about individuals. For health topics, do not present supplements or foods as treatments, imply diagnosis, promise outcomes, or advise users to replace professional care or medication. # Actor input Schema ## `mode` (type: `string`): Start with the demo, analyze uploaded data without a Cookie, or collect with your own Xiaohongshu session. ## `cookie` (type: `string`): Required for note, search, and creator-post API modes. Never included in output or logs. ## `query` (type: `string`): The category, consumer topic, or keyword being researched. ## `uploadedNotes` (type: `array`): Paste note records exported from any compatible Xiaohongshu Actor. Used by all intelligence modes. ## `uploadedComments` (type: `array`): Paste comment records or strings. Common text/content/comment, id/commentId, noteId, and URL fields are recognized. ## `knownEntities` (type: `array`): Names to measure in consumer discussions, for example brands, products, ingredients, devices, medicines, foods, or lifestyle alternatives. ## `regulatedTopic` (type: `boolean`): Adds claim-risk evidence and safer framing. This is a screening aid, not legal or medical approval. ## `maxEvidence` (type: `integer`): Maximum number of consumer questions and supporting excerpts returned in a report. ## `brandDatasets` (type: `array`): For brand comparison without a Cookie: \[{"brand":"A","notes":\[...]},{"brand":"B","notes":\[...]}]. ## `maxOpportunities` (type: `integer`): Maximum ranked ideas returned by content opportunity radar. Each returned opportunity is a paid event. ## `noteUrlOrId` (type: `string`): A Xiaohongshu note URL (keep xsec\_token when present) or note ID. ## `userUrlOrId` (type: `string`): Required in creator posts mode. ## `proxyConfiguration` (type: `object`): Residential proxy is recommended for authenticated modes. ## `startUrls` (type: `array`): Public Xiaohongshu note URLs to analyze. ## `htmlSnapshots` (type: `array`): Optional saved pages for testing or authorized snapshot workflows. ## `brandKeywords` (type: `array`): Case-insensitive terms used to identify relevant notes. ## `maxItems` (type: `integer`): Stops after this many successfully parsed, unique notes. ## `requestDelayMs` (type: `integer`): Polite delay between public-page requests. ## Actor input object example ```json { "mode": "demo", "uploadedNotes": [], "uploadedComments": [], "knownEntities": [], "regulatedTopic": false, "maxEvidence": 20, "brandDatasets": [], "maxOpportunities": 10, "proxyConfiguration": { "useApifyProxy": false }, "startUrls": [], "htmlSnapshots": [], "brandKeywords": [], "maxItems": 100, "requestDelayMs": 1500 } ``` # Actor output Schema ## `results` (type: `string`): No description ## `reports` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("scrupulous_buckler/xiaohongshu-brand-influencer-discovery").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("scrupulous_buckler/xiaohongshu-brand-influencer-discovery").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call scrupulous_buckler/xiaohongshu-brand-influencer-discovery --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrupulous_buckler/xiaohongshu-brand-influencer-discovery", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Xiaohongshu / RedNote Scraper & Intelligence", "description": "Scrape or analyze Xiaohongshu and RedNote notes and comments for content opportunities, creator audits, competitor comparisons, consumer voice insights, and market maps. Use uploaded datasets without cookies or collect notes with your own session.", "version": "0.1", "x-build-id": "xwoFqyWdbqTWS0utE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrupulous_buckler~xiaohongshu-brand-influencer-discovery/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrupulous_buckler-xiaohongshu-brand-influencer-discovery", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrupulous_buckler~xiaohongshu-brand-influencer-discovery/runs": { "post": { "operationId": "runs-sync-scrupulous_buckler-xiaohongshu-brand-influencer-discovery", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrupulous_buckler~xiaohongshu-brand-influencer-discovery/run-sync": { "post": { "operationId": "run-sync-scrupulous_buckler-xiaohongshu-brand-influencer-discovery", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "mode": { "title": "Analysis or collection mode", "enum": [ "demo", "topicRadar", "consumerVoice", "marketMap", "creatorAudit", "brandCompare", "snapshot", "note", "search", "userPosts" ], "type": "string", "description": "Start with the demo, analyze uploaded data without a Cookie, or collect with your own Xiaohongshu session.", "default": "demo" }, "cookie": { "title": "Xiaohongshu Cookie (secret)", "type": "string", "description": "Required for note, search, and creator-post API modes. Never included in output or logs." }, "query": { "title": "Topic or search keyword", "type": "string", "description": "The category, consumer topic, or keyword being researched." }, "uploadedNotes": { "title": "Existing note data (no Cookie required)", "type": "array", "description": "Paste note records exported from any compatible Xiaohongshu Actor. Used by all intelligence modes.", "default": [] }, "uploadedComments": { "title": "Existing comment data (no Cookie required)", "type": "array", "description": "Paste comment records or strings. Common text/content/comment, id/commentId, noteId, and URL fields are recognized.", "default": [] }, "knownEntities": { "title": "Brands, products, ingredients, and alternatives", "type": "array", "description": "Names to measure in consumer discussions, for example brands, products, ingredients, devices, medicines, foods, or lifestyle alternatives.", "default": [], "items": { "type": "string" } }, "regulatedTopic": { "title": "Regulated health or other sensitive topic", "type": "boolean", "description": "Adds claim-risk evidence and safer framing. This is a screening aid, not legal or medical approval.", "default": false }, "maxEvidence": { "title": "Maximum evidence excerpts", "minimum": 5, "maximum": 100, "type": "integer", "description": "Maximum number of consumer questions and supporting excerpts returned in a report.", "default": 20 }, "brandDatasets": { "title": "Brand datasets", "type": "array", "description": "For brand comparison without a Cookie: [{\"brand\":\"A\",\"notes\":[...]},{\"brand\":\"B\",\"notes\":[...]}].", "default": [] }, "maxOpportunities": { "title": "Maximum content opportunities", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum ranked ideas returned by content opportunity radar. Each returned opportunity is a paid event.", "default": 10 }, "noteUrlOrId": { "title": "Note URL or ID", "type": "string", "description": "A Xiaohongshu note URL (keep xsec_token when present) or note ID." }, "userUrlOrId": { "title": "Creator profile URL or user ID", "type": "string", "description": "Required in creator posts mode." }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Residential proxy is recommended for authenticated modes.", "default": { "useApifyProxy": false } }, "startUrls": { "title": "Public note URLs", "type": "array", "description": "Public Xiaohongshu note URLs to analyze.", "default": [], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "htmlSnapshots": { "title": "HTML snapshots", "type": "array", "description": "Optional saved pages for testing or authorized snapshot workflows.", "default": [] }, "brandKeywords": { "title": "Brand or category keywords", "type": "array", "description": "Case-insensitive terms used to identify relevant notes.", "default": [], "items": { "type": "string" } }, "maxItems": { "title": "Maximum successful results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Stops after this many successfully parsed, unique notes.", "default": 100 }, "requestDelayMs": { "title": "Delay between requests", "minimum": 500, "maximum": 10000, "type": "integer", "description": "Polite delay between public-page requests.", "default": 1500 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```